Cv2 Python Tutorial – Complete Guide

As we navigate through the world of coding and game development, we often stumble upon techniques that add new dimensions to our projects. One such technique is computer vision, a field within artificial intelligence that leads us into extracting, processing, and understanding data from images or multi-dimensional data from the real world. And while delving into it, the library ‘cv2’ in Python often becomes the cornerstone tool for many. But what is cv2 in Python? Why should you learn it? Let’s find out.

What is cv2 in Python?

‘cv2’ is OpenCV’s python library which hosts an extensive collection of over 2500 optimized algorithms – both classic and state-of-the-art computer vision and machine learning. Created to realize the full potential of computer vision, cv2 in Python facilitates easy integration of real-world data to help machines perceive visuals like a human.

Why should you learn cv2 Python?

There are several compelling reasons to learn cv2. Computer vision is driving future technologies and this Python library is a stepping stone into that future. Some of the key reasons to learn cv2 Python include:

  • Extensive functionalities: cv2 Python offers a vast array of processing and manipulation functionalities for computer vision.
  • Real-time operations: Cv2 Python can be applied to real-time operations while being highly efficient.
  • Machine Learning Implementation: The implementation of machine learning algorithms in Cv2 Python makes automated vision possible.
  • Boost your portfolio: Knowledge of computer vision and cv2 Python can give a massive boost to your portfolio if you’re venturing into game development, AI or data science.

Let’s now understand how we can utilize cv2 Python by delving into some coding examples.

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Getting Started with cv2 Python

The first step to using cv2 is to install it. Here’s how we do it using pip:

pip install opencv-python

Next, let’s load an image using cv2:

import cv2
image = cv2.imread('image.jpg',1)

The ‘imread’ function loads the image from the specified file in your system. The second parameter determines how the image should be read.

  • cv2.IMREAD_COLOR : Loads a color image.
  • cv2.IMREAD_GRAYSCALE : Loads image in grayscale mode
  • cv2.IMREAD_UNCHANGED : Loads image as such including alpha channel.

Image Manipulation With cv2

cv2 offers various functionalities for manipulating images. Below are some examples.

Converting an image to grayscale

grayscale_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

Resizing an image

resized_image = cv2.resize(image, (new_width, new_height))

Applying Gaussian blur

blurred_image = cv2.GaussianBlur(image, (kernel_width, kernel_height), 0)

Detecting edges

edges = cv2.Canny(image, low_threshold, high_threshold)

These are just a few examples of the many operations you can perform on images using cv2 in Python. The library is incredibly powerful and opens up a vast range of possibilities.

Analyzing Images with cv2

Beyond just manipulating images, cv2 also offers tools for analyzing images. Let’s look at some examples:

Finding contours in an image

contours, hierarchy = cv2.findContours(image, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

This function is used to detect and draw contours in binary image. The output contours are a Python list of all the contours in the image.

Drawing circles, rectangles and lines on images

Cv2 allows you to draw various shapes on images. Here are examples of how to draw a circle, rectangle, and line:

# Drawing a circle, (x_center, y_center), radius, (B,G,R), thickness)

# Drawing a rectangle
cv2.rectangle(image, (x1, y1), (x2, y2), (B,G,R), thickness)

# Drawing a line
cv2.line(image, (x1, y1), (x2, y2), (B,G,R), thickness)

Getting image properties

# Image properties include number of rows, columns, channels, type of image data, number of pixels, etc.

# shape of image

# total number of pixels

# image datatype

Detecting corners

corners = cv2.goodFeaturesToTrack(gray_image, maxCorners, qualityLevel, minDistance)

This function determines the corners of the image. The parameters maxCorners, qualityLevel and minDistance determines the number of corners, the minimum accepted quality of corners and minimum possible Euclidean distance between the returned corners.

This just scratches the surface of all that you can do with cv2 in Python. As you can see, this powerful library can help you to analyze and manipulate images in countless ways, supporting your entry into the exciting world of computer vision!

Where to go next? Keep Learning!

Your journey into the ever-intriguing world of computer vision and Python doesn’t have to end here. We encourage you to continue to explore, learn, and implement your newfound knowledge. A great next step would be to dive into our Python Mini-Degree.

The Python Mini-Degree offered by Zenva Academy is a comprehensive collection of Python courses. This collection takes you from learning the core aspects of coding in Python to exploring complex topics like algorithms, object-oriented programming, game development, and app development. By completing these courses, you not only gain a deeper understanding of Python, but also get the opportunity to create your own Python projects and boost your coding portfolio.

One of the notable aspects of Python is its high demand in the job market, particularly in thriving fields like data science and game development. With the Python Mini-Degree, you can acquire the skills to unlock opportunities in such promising domains. Designed to cater to learners of varying skill levels. courses include interactive lessons, coding challenges, and supporting quizzes to reinforce learning while ensuring progress at a comfortable pace.

Beyond the Python Mini-Degree, we offer numerous other courses that focus on Python. We invite you to explore our broad collection of Python courses.


In conclusion, cv2 Python is a powerful and versatile tool for anyone interested in computer vision or looking to add a new dimension to their game development and data science projects. The possibilities with cv2 Python are vast and the more you dive into it, the more you’ll realize its potential.

For those ready to embark on this exciting journey, our Python Mini-Degree is the perfect launch pad. It encapsulates the core aspects of Python including libraries like cv2, giving you a holistic learning experience. Start your transformation from a coding enthusiast to a professional developer with us at Zenva today!

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